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OBJECTIVE To explore the effect of volatile oil of Ligusticum chuanxiong on the transdermal properties and cytotoxicity of triptolide in vitro. METHODS The chemical constituents of the volatile oil of L. chuanxiong were analyzed by gas chromatography-mass spectrometry. The lower abdominal skin of KM mice was separated and divided into triptolide group， triptolide in compatibility with volatile oil of L. chuanxiong groups at 1∶10， 1∶50， 1∶100 （hereinafter referred to as “compatibility 1∶10”“compatibility 1∶50”“compatibility 1∶100” groups）. After the skin of mice in each group was fully exposed to 0.2 g of the corresponding cream for 24 h， the cumulative transdermal dose （Qn） of triptolide in the receiving solution of each group was determined by high-performance liquid chromatography， and the transdermal absorption rate （Jss） was calculated. Human immortalized keratinocytes （HaCat） were used as a model， the CCK-8 method was used to detect the cell survival rate of different concentrations of the volatile oil of L. chuanxiong and triptolide before and after compatibility. RESULTS A total of 62 chemical constituents of the volatile oil of L. chuanxiong were identified， including Z-ligustilide， senkyunolide， and β-selinene. The Qn （P＜ 0.01） and Jss of triptolide increased within 24 h in the compatibility 1∶10 and 1∶50 groups， while the Qn （P＜0.05） and Jss decreased in the compatibility 1∶100 group as compared with the triptolide group. Compared with the triptolide group， the cell survival rate of HaCat was significantly increased in the compatibility 1∶10 and 1∶50 groups when the triptolide concentrations were 36， 72 and 144 ng/mL （P＜0.05 or P＜0.01）； while the cell survival rate of HaCat was decreased in the compatibility 1∶100 group， but the difference was not statistically significant （P＞0.05）. CONCLUSIONS When the compatibility ratio of triptolide and volatile oil of L. chuanxiong was 1∶10 or 1∶50， it can promote the transdermal absorption of triptolide and reduce the cytotoxicity of triptolide to HaCat.
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ObjectiveCoronavirus disease 2019 (COVID-19) is a serious infectious disease, which has caused great number of deaths and health problems worldwide. This study aims to examine the effects of airborne particulate matter (PM) pollution on COVID-19 across China. MethodsIn this study, we obtained confirmed cases of COVID-19, the data of airborne ambient PM with aerodynamic diameter [≤] 2.5 m (PM2.5) and [≤] 10 m (PM10), ambient temperature (AT), absolute humidity (AH) and migration scale index (MSI) in 72 cities of China (excluded Wuhan city) on a daily basis, each of which confirmed more than 50 cases from January 20th to March 2nd, 2020. We applied a two-stage analysis. Generalized additive models with quasi-Poisson distribution was first fitted to estimate city-specific effects of PM10 and PM2.5 on daily confirmed COVID-19 cases while controlling AT, AH and MSI. Then, we used meta-analysis to generate the pooled effect estimates from city-specific results. ResultsDuring the study period, there were a total of 24 939 COVID-19 cases, most of which were reported in Hubei Province. In our meta-analysis, we found each 10 g/m3 increase in concentration of PM2.5 and PM10 in single day lag (from lag 0 to lag 7 and lag 14) were positively associated with confirmed cases of COVID-19, not including PM10 at lag 5, lag 6 and lag 7, and PM2.5 at lag 5, lag 6. Similar trend was also found in different cumulative lag days (from lag 01 to lag 07 and lag 014). The effects of PM2.5 and PM10 on daily COVID-19 confirmed cases are statistically significant for three cumulative lag periods over 3, 7 and 14 days with the greatest effect over 14 days. The estimated RRs of which were 1.64 (95% CIs: 1.47, 1.82) and 1.47 (95% CIs: 1.34, 1.61) with each 10 g/m3 increase in concentrations of PM2.5 and PM10, respectively. In addition, we found that the effects of PM2.5 on daily confirmed cases were greater than PM10 in all included lag days. ConclusionsThis nationwide study suggests that airborne PM pollution likely increases the risk of getting COVID-19 in China.
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ObjectMeteorological parameters are the important factors influencing the infectious diseases like severe acute respiratory syndrome (SARS). This study aims to explore the association between coronavirus disease (COVID-19) death and weather parameters. MethodsIn this study, we collected the daily death number of COVID-19, meteorological and air pollutant data from 20 January, 2020 to 29 February, 2020 in Wuhan, China. Then, the generalized additive model was applied to explore the impact of temperature, humidity and diurnal temperature range on daily mortality of COVID-19. ResultsThere were in total 2299 COVID-19 mortality counts in Wuhan. A positive association with COVID-19 mortality was observed for diurnal temperature range (r = 0.44), but negative association for relative humidity (r = -0.32). In addition, each 1 unit increase in diurnal temperature range was only associated with a 2.92% (95% CI: 0.61%, 5.28%) increase in COVID-19 mortality at lag 3. However, both per 1 unit increase of temperature and absolute humidity were related to the decreased COVID-19 mortality at lag 3 and lag 5, respectively. ConclusionIn summary, this study suggests the temperature variation and humidity may be important factors affecting the COVID-19 mortality.
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[Summary] This article reviewed the clinical features in two diabetes cases complicated with nasal‐brain mucormycosis by pathology and pulmonary mucormycosis. In one patient with diabetes combined with pulmonary mucormycosis ,manifestations of chest pain and hemoptysis ,the right upper lung biopsy tip morphology was consistent with Mucor ,successfully cured with amphotericin and operation treatment. The other patient with diabetes‐complicated nasal mucormycosis with headache and nasal cavity clump , showed black caseous matter ,finally hemiplegia. A nasal cavity tumor was proved by pathological examination. After treatment with fluconazole and operation ,the patientdied. Mucormycosisis rare and may be secondary to diabetes and hypoimmunity disease. It needs rapid diagnosis and treatment.
